• 한국정보디스플레이학회:학술대회논문집
• /
• 2007.08b
• /
• pp.1245-1248
• /
• 2007

We propose new approaches to thin film transistor fabrication that use carbon nanotubes and semiconductor nanowires as active elements. These nanomaterials which are essentially studied in the context of the post CMOS era will certainly impact the active matrix display industry in the near future.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2005.07b
• /
• pp.867-872
• /
• 2005

High-pixel-density displays are now under development to meet the needs of next-generation mobile devices; methods to more efficiently build such displays are described. Displays based on subpixel rendering and RGBW technologies, known as PenTile $Matrix^{TM}$ RGBW, are shown to offer the best approach to meeting the demanding requirements of low manufacturing cost, high brightness, and low power.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.10a
• /
• pp.289-292
• /
• 1996

In Cholesky factorization of the interior point method, dense columns of A matrix make dense Cholesky factor L regardless of sparsity of A matrix. We introduce a method to transform a primal problem to a dual problem in order to preserve the sparsity.

• Communications for Statistical Applications and Methods
• /
• v.10 no.1
• /
• pp.233-237
• /
• 2003

An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.

• Information and Communications Magazine
• /
• v.7 no.3
• /
• pp.27-34
• /
• 1990

The $(L,\psi)$ feature description on the binary boundary air craft image is introduced of classifying 3-D object (aircraft) identification. Three types for associative matrix memories are employed and tested for their classification performance. The fast association involved in these memories can be implemented using a parallel optical matrix-vector operation. Two associative memories are based on pseudoinverse solutions and the third one is interoduced as a paralell version of a nearest-neighbor classifier. Detailed simulation results for each associative processor are provided.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.25-28
• /
• 2001

A theory of binary wavelets has been recently proposed by using two-band perfect reconstruction filter banks over binary field . Binary wavelet transform (BWT) of binary images can be used as an alternative to the real-valued wavelet transform of binary images in image processing applications such as compression, edge detection, and recognition. The BWT, however, requires large amount of computations since its operation is accomplished by matrix multiplication. In this paper, a fast BWT algorithm which utilizes filtering operation instead or matrix multiplication is presented . It is shown that the proposed algorithm can significantly reduce the computational complexity of the BWT. For the decomposition and reconstruction or an N ${\times}$ N image, the proposed algorithm requires only 2LN$^2$ multiplications and 2(L-1)N$^2$addtions when the filter length is L, while the BWT needs 2N$^3$multiplications and 2N(N-1)$^2$additions.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.3
• /
• pp.32-39
• /
• 2009

A new discrete time gain-scheduled control design is proposed to improve disturbance attenuation for systems with bounded control input under known disturbance maximum norm. The state feedback gains are scheduled according to the proximity of the state of the plant to the origin. The controllers are derived in the framework of linear matrix inequality(LMI) optimization. This procedure yields a linear time varying control structure that allows higher gain and hence higher performance controllers as the state moves closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition under the given disturbance maximum norm.

• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.6 s.183
• /
• pp.81-87
• /
• 2006

A new gain-scheduled control design is proposed to improve disturbance attenuation for systems with bounded control input. The state feedback controller is scheduled according to the proximity to the origin of the state of the plant. The controllers is derived in the framework of linear matrix inequality(LMI) optimization. This procedure yields a linear time varying control structure that allows higher gain and hence higher performance controllers as the state move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• MALSORI
• /
• no.66
• /
• pp.105-116
• /
• 2008

In this research, we propose a speaker identification system using a kernel method which is expected to model the non-linearity of speech features well. We have been using principal component analysis (PCA) successfully, and extended to kernel PCA, which is used for many pattern recognition tasks such as face recognition. However, we cannot use kernel PCA for speaker identification directly because the storage required for the kernel matrix grows quadratically, and the computational cost grows linearly (computing eigenvector of $l{\times}l$ matrix) with the number of training vectors I. Therefore, we use greedy kernel PCA which can approximate kernel PCA with small representation error. In the experiments, we compare the accuracy of the greedy kernel PCA with the baseline Gaussian mixture models using MFCCs and PCA. As the results with limited enrollment data show, the greedy kernel PCA outperforms conventional methods.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2006.03a
• /
• pp.752-759
• /
• 2006

Conglomerates and core-stones are the typical composite geomaterials that are composed of a weak matrix and a strong pebble part. In general, we couldn't analyze the composite geomaterials by using emperical rock classification methods. In the study, a series of analyses of elastic behavior of composite geomaterials are carried out by using homogenization theory. 45-case models are made with considering 3 kind of factors such as gravel content, size and strength of matrix. Those are applicable to various composite geomaterials of conglomerates and core-stones. The size of analysis model is large enough to exceed REV.